Frequently asked questions

browser-memory is a persistent, per-site memory layer for AI browsing agents. Every DOM selector and XHR request an agent works out becomes a reusable, installable skill in a shared catalog, kept current and repaired for everyone. Instead of re-reading a page on every run, your agent calls a saved tool and gets structured data back.

A raw agent screenshots the page, snapshots the DOM, guesses selectors, and re-derives the same actions on every run. browser-memory replaces that with a single call to a pre-built skill that returns structured data, so typical runs are about 20× faster and use roughly 4× fewer tokens.

Install one skill at a time with the bmem CLI: run `bmem add {site}/{task}`. Your agent can also request any missing skill on the fly — it is generated and tested in your browser, then shipped to the shared catalog. Self-hosting the catalog is free and unlimited.

Yes. browser-memory exposes every skill over the Model Context Protocol (MCP), so Claude Code and any other MCP-capable browsing agent can discover and run them directly, alongside a normal browser.

Frameworks like browser-use and low-level servers like Playwright MCP drive the browser live and re-learn each page every run. browser-memory is the layer underneath: a shared memory of pre-built, self-repairing skills that any agent reuses. See the full comparisons at /vs/browser-use and /vs/playwright-mcp.

An AI browsing agent is a program that uses a large language model to operate a web browser on your behalf — navigating pages, filling forms, extracting data, and completing tasks the way a person would. browser-memory gives that agent a persistent, per-site memory, so it stops figuring out each site from scratch on every run.

Self-hosting the catalog is free and unlimited, forever. You install skills with the bmem CLI and run them against your own browser, so there is no per-run cost to get started.

The shared catalog grows as agents use it — every site an agent learns becomes reusable for everyone. It already covers targets like LinkedIn, X and Reddit for outreach, plus shopping, travel and research sites, and any missing site can be learned on the fly. Browse the full, live list in the ecosystem catalog.

Because every agent shares one catalog, the first agent to hit a broken skill triggers a repair: a subagent rebuilds and re-tests the tool in the browser, and the fix ships to the shared memory for everyone. You do not each fix the same breakage separately.

No. You install a skill with a single `bmem add {site}/{task}` command and your agent calls it. When a skill is missing, the agent requests it and browser-memory generates and tests it automatically — you do not have to write selectors or scripts yourself.